Wang Rendong, Zhao Lei, Wang Shijia, Zhao Xiaoxiao, Liang Chuanyu, Wang Pei, Li Dongguo
School of Biomedical Engineering, Capital Medical University, Beijing, China.
Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical, Capital Medical University, Beijing, China.
Front Genet. 2022 Sep 19;13:989985. doi: 10.3389/fgene.2022.989985. eCollection 2022.
Glioblastoma (GBM) is characterized by extensive genetic and phenotypic heterogeneity. However, it remains unexplored primarily how CpG island methylation abnormalities in promoter mediate glioblastoma typing. First, we presented a multi-omics scale map between glioblastoma sample clusters constructed based on promoter CpG island (PCGI) methylation-driven genes, using datasets including methylation profiles, expression profiles, and single-cell sequencing data from multiple highly annotated public clinical cohorts. Second, we identified differences in the tumor microenvironment between the two glioblastoma sample clusters and resolved key signaling pathways between cell clusters at the single-cell level based on comprehensive comparative analyses to investigate the reasons for survival differences between two of these clusters. Finally, we developed a diagnostic map and a prediction model for glioblastoma, and compared theoretical differences of drug sensitivity between two glioblastoma sample clusters. In summary, this study established a classification system for dissecting promoter CpG island methylation heterogeneity in glioblastoma and provides a new perspective for the diagnosis and treatment of glioblastoma.
胶质母细胞瘤(GBM)具有广泛的基因和表型异质性。然而,启动子中的CpG岛甲基化异常如何介导胶质母细胞瘤分型,这一问题仍未得到充分探索。首先,我们利用来自多个高度注释的公共临床队列的甲基化谱、表达谱和单细胞测序数据等数据集,构建了基于启动子CpG岛(PCGI)甲基化驱动基因的胶质母细胞瘤样本簇之间的多组学规模图谱。其次,我们识别了两个胶质母细胞瘤样本簇之间肿瘤微环境的差异,并基于全面的比较分析在单细胞水平解析了细胞簇之间的关键信号通路,以探究其中两个簇生存差异的原因。最后,我们开发了胶质母细胞瘤的诊断图谱和预测模型,并比较了两个胶质母细胞瘤样本簇之间药物敏感性的理论差异。总之,本研究建立了一个用于剖析胶质母细胞瘤启动子CpG岛甲基化异质性的分类系统,并为胶质母细胞瘤的诊断和治疗提供了新的视角。